activity
20152022
most citedConvolutional Neural Network Architectures for Matching Natural Language Sentences

972 citations · 1k across the 9 of their papers we have counts for

collaborators

14 papers

cs.CL2022

Calibration Meets Explanation: A Simple and Effective Approach for Model Confidence Estimates

Dongfang Li, Baotian Hu, Qingcai Chen

Calibration strengthens the trustworthiness of black-box models by producing better accurate confidence estimates on given examples. However, little is known about if model explana…

cs.CL20226 cited

Prompt-based Text Entailment for Low-Resource Named Entity Recognition

Dongfang Li, Baotian Hu, Qingcai Chen

Pre-trained Language Models (PLMs) have been applied in NLP tasks and achieve promising results. Nevertheless, the fine-tuning procedure needs labeled data of the target domain, ma…

cs.CL20222 cited

An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks

Yuxiang Wu, Yu Zhao, Baotian Hu +3

Access to external knowledge is essential for many natural language processing tasks, such as question answering and dialogue. Existing methods often rely on a parametric model tha…

cs.AI20214 cited

GlyphCRM: Bidirectional Encoder Representation for Chinese Character with its Glyph

Yunxin Li, Yu Zhao, Baotian Hu +5

Previous works indicate that the glyph of Chinese characters contains rich semantic information and has the potential to enhance the representation of Chinese characters. The typic…

cs.CL2021

Multi-hop Graph Convolutional Network with High-order Chebyshev Approximation for Text Reasoning

Shuoran Jiang, Qingcai Chen, Xin Liu +2

Graph convolutional network (GCN) has become popular in various natural language processing (NLP) tasks with its superiority in long-term and non-consecutive word interactions. How…

cs.CL2021

You Can Do Better! If You Elaborate the Reason When Making Prediction

Dongfang Li, Jingcong Tao, Qingcai Chen +1

Neural predictive models have achieved remarkable performance improvements in various natural language processing tasks. However, most neural predictive models suffer from the lack…